摘要：Based on the general model of design optimization of multibody dynamics, a modified genetic algorithm with adaptive crossover and mutation rates is developed to find optimal design variables which satisfy the dynamic constraints and obtain optimum objective values. Generalized-α projection method and higher order variational integrators with Lagrangian polynomial and Gauss quadrature formula are used to solve differential–algebraic equations during optimization process. Efficiency and accuracy of the numerical results obtained by intelligent design optimization with different differential–algebraic equation solving methods are compared.
